Discussions With Physicians About Hospice Among Patients With Metastatic Lung Cancer
Bibliographic record
Abstract
BACKGROUND: Many terminally ill patients enroll in hospice only in the final days before death or not at all. Discussing hospice with a health care provider could increase awareness of hospice and possibly result in earlier use. METHODS: We used data on 1517 patients diagnosed as having stage IV lung cancer from a multiregional study. We estimated logistic regression models for the probability that a patient discussed hospice with a physician or other health care provider before an interview 4 to 7 months after diagnosis as reported by either the patient or surrogate or documented in the medical record. RESULTS: Half (53%) of the patients had discussed hospice with a provider. Patients who were black, Hispanic, non-English speaking, married or living with a partner, Medicaid beneficiaries, or had received chemotherapy were less likely to have discussed hospice. Only 53% of individuals who died within 2 months after the interview had discussed hospice, and rates were lower among those who lived longer. Patients who reported that they expected to live less than 2 years had much higher rates of discussion than those expecting to live longer. Patients reporting the most severe pain or dyspnea were no more likely to have discussed hospice than those reporting less severe or no symptoms. A third of patients who reported discussing do-not-resuscitate preferences with a physician had also discussed hospice. CONCLUSIONS: Many patients diagnosed as having metastatic lung cancer had not discussed hospice with a provider within 4 to 7 months after diagnosis. Increased communication with physicians could address patients' lack of awareness about hospice and misunderstandings about prognosis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".